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Abstract:

A method that includes: (i) detecting an acoustic wave that is
propagating through a body of water, as the body of water is being frozen
on a structure, thus yielding a detected acoustic wave; (ii) extracting,
from the detected acoustic wave, (a) a frequency component thereof, and
(b) a magnitude of the frequency component; and (iii) removing the body
of water from the structure when the magnitude exceeds a threshold value.

Claims:

1. A method comprising: detecting an acoustic wave that is propagating
through a body of water, as said body of water is being frozen on a
structure, thus yielding a detected acoustic wave; extracting, from said
detected acoustic wave, (a) a frequency component thereof, and (b) a
magnitude of said frequency component; and removing said body of water
from said structure when said magnitude exceeds a threshold value.

2. The method of claim 1, wherein said detected acoustic wave is a
time-domain signal, and wherein said extracting comprises: transforming
said time-domain signal to a frequency-domain signal; and obtaining said
frequency component, and said magnitude, from said frequency-domain
signal.

3. The method of claim 1, wherein said threshold value is a first
threshold value, wherein said extracting also extracts (a) a harmonic of
said frequency component, and (b) a magnitude of said harmonic, and
wherein said removing is performed when both of (i) said magnitude
exceeds said first threshold value, and (ii) said magnitude of said
harmonic exceeds a second threshold value.

4. A system comprising: a detector that detects an acoustic wave that is
propagating through a body of water, as said body of water is being
frozen on a structure, thus yielding a detected acoustic wave; and a
processor that: extracts, from said detected acoustic wave, (a) a
frequency component thereof, and (b) a magnitude of said frequency
component; and issues a signal to remove said body of water from said
structure when said magnitude exceeds a threshold value.

5. The system of claim 4, wherein said detected acoustic wave is a
time-domain signal, and wherein said processor, to extract said frequency
component and said magnitude: transforms said time-domain signal to a
frequency-domain signal; and obtains said frequency component, and said
magnitude, from said frequency-domain signal.

6. The system of claim 4, wherein said threshold value is a first
threshold value, and wherein said processor: also extracts, from said
detected acoustic wave, (a) a harmonic of said frequency component, and
(b) a magnitude of said harmonic; and issues said signal when both of (i)
said magnitude exceeds said first threshold value, and (ii) said
magnitude of said harmonic exceeds a second threshold value.

7. A storage medium comprising instructions that are readable by a
processor, and that when read by said processor cause said processor to:
extract, from a detected acoustic wave, (a) a frequency component
thereof, and (b) a magnitude of said frequency component, wherein said
detected acoustic wave represents an acoustic wave that is propagating
through a body of water, as said body of water is being frozen on a
structure; and issue a signal to remove said body of water from said
structure when said magnitude exceeds a threshold value.

8. The storage medium of claim 7, wherein said detected acoustic wave is
a time-domain signal, and wherein said processor, to extract said
frequency component and said magnitude: transforms said time-domain
signal to a frequency-domain signal; and obtains said frequency
component, and said magnitude, from said frequency-domain signal.

9. The storage medium of claim 7, wherein said threshold value is a first
threshold value, and wherein said processor: also extracts, from said
detected acoustic wave, (a) a harmonic of said frequency component, and
(b) a magnitude of said harmonic; and issues said signal when both of (i)
said magnitude exceeds said first threshold value, and (ii) said
magnitude of said harmonic exceeds a second threshold value.

10. A method comprising: detecting an acoustic wave that is propagating
through a body of water, as said body of water is being frozen on a
structure in an ice-making machine, thus yielding a detected acoustic
wave; analyzing said detected acoustic wave to yield a spectrum thereof;
determining whether said spectrum includes a spectral signature that is
present when a device in said ice-making machine is operating, thus
yielding a determination; and issuing an alert based on said
determination.

11. The method of claim 10, wherein said issuing comprises issuing said
alert if said determination indicates that said spectrum does not include
said spectral signature.

12. The method of claim 10, wherein said detected acoustic wave is a
time-domain signal, and wherein said analyzing comprises: transforming
said time-domain signal to a frequency-domain signal; and obtaining said
spectrum from said frequency-domain signal.

13. A system comprising: a detector that detects an acoustic wave that is
propagating through a body of water, as said body of water is being
frozen on a structure in an ice-making machine, thus yielding a detected
acoustic wave; and a processor that: analyzes said detected acoustic wave
to yield a spectrum thereof; determines whether said spectrum includes a
spectral signature that is present when a device in said ice-making
machine is operating, thus yielding a determination; and issues an alert
based on said determination.

14. The system of claim 13, wherein said processor issues said alert if
said determination indicates that said spectrum does not include said
spectral signature.

15. The system of claim 13, wherein said detected acoustic wave is a
time-domain signal, and wherein to analyze said detected acoustic wave,
said processor: transforms said time-domain signal to a frequency-domain
signal; and obtains said spectrum from said frequency-domain signal.

16. A storage medium comprising instructions that are readable by a
processor, and that when read by said processor cause said processor to:
analyze a detected acoustic wave to yield a spectrum thereof, wherein
said detected acoustic wave represents an acoustic wave that is
propagating through a body of water, as said body of water is being
frozen on a structure in an ice-making machine; determine whether said
spectrum includes a spectral signature that is present when a device in
said ice-making machine is operating, thus yielding a determination; and
issue an alert based on said determination.

17. The storage medium of claim 16, wherein said processor issues said
alert if said determination indicates that said spectrum does not include
said spectral signature.

18. The storage medium of claim 16, wherein said detected acoustic wave
is a time-domain signal, and wherein to analyze said detected acoustic
wave, said processor: transforms said time-domain signal to a
frequency-domain signal; and obtains said spectrum from said
frequency-domain signal.

19. The system of claim 4, wherein said detector comprises a microphone
in a probe that is situated less than 0.5 inches from said structure.

20. The system of claim 4, wherein said detector comprises a microphone
in a probe that is in contact with said structure.

21. The system of claim 4, wherein said detector comprises a microphone
in a probe that is situated less than 0.5 inches from said body of water.

22. The system of claim 4, wherein said detector comprises a microphone
in a probe that is in contact with said body of water.

23. The system of claim 13, wherein said detector comprises a microphone
in a probe that is situated less than 0.5 inches from said structure.

24. The system of claim 13, wherein said detector comprises a microphone
in a probe that is in contact with said structure.

25. The system of claim 13, wherein said detector comprises a microphone
in a probe that is situated less than 0.5 inches from said body of water.

26. The system of claim 13, wherein said detector comprises a microphone
in a probe that is in contact with said body of water.

Description:

COPYRIGHT NOTICE

[0001] A portion of the disclosure of this patent document contains
material that is subject to copyright protection. The copyright owner has
no objection to the facsimile reproduction by anyone of the patent
document or the patent disclosure, as it appears in the Patent and
Trademark Office patent files or records, but otherwise reserves all
copyright rights whatsoever.

BACKGROUND

[0002] 1. Field

[0003] The present disclosure relates to an ice-making machine, and more
particularly, to an analysis of an acoustic wave that is propagating
through a body of water in the ice-making machine. The analysis
recognizes when the body of water is frozen, so that the body of water
can be harvested, as ice, from the ice-making machine. The analysis also
diagnoses operations of devices in the ice-making machine.

[0004] 2. Description of the Related Art

[0005] The approaches described in this section are approaches that could
be pursued, but not necessarily approaches that have been previously
conceived or pursued. Therefore, unless otherwise indicated, the
approaches described in this section may not be prior art to the claims
in this application and are not admitted to be prior art by inclusion in
this section.

[0006] For efficient operation of an ice-making machine, it is desirable
to remove the ice, also known as harvesting the ice, soon after the ice
has fully formed. Such harvesting of the ice allows for a new body of
water to be introduced so that a new body of ice can be formed, thus
maximizing the usage of the ice-making machine.

[0007] One technique for recognizing the readiness of the ice for
harvesting is to monitor a magnitude of a mechanical vibration that is
propagating through a body of water as the body of water is being frozen.
At a point in time when the magnitude exceeds a predetermined threshold,
the body of water is assumed to be adequately frozen, and so, is
harvested.

[0008] This existing technique uses only amplitude change above a set
threshold to detect ice formation. This technique has a drawback in that
it does not distinguish between various possible sources of mechanical
vibrations, and so, cannot determine whether the change is due to a
change in acoustics of the ice-making machine or spurious acoustics in an
ambient noise environment. Consequently, the existing technique does not
necessarily initiate harvesting at a most optimum time, and therefore,
the ice-making machine may be operating at a less than optimum level of
efficiency.

SUMMARY

[0009] There is provided a method that includes: (i) detecting an acoustic
wave that is propagating through a body of water, as the body of water is
being frozen on a structure, thus yielding a detected acoustic wave; (ii)
extracting, from the detected acoustic wave, (a) a frequency component
thereof, and (b) a magnitude of the frequency component; and (iii)
removing the body of water from the structure when the magnitude exceeds
a threshold value.

[0010] There is also provided a method that includes: (a) detecting an
acoustic wave that is propagating through a body of water, as the body of
water is being frozen on a structure in an ice-making machine, thus
yielding a detected acoustic wave; (b) analyzing the detected acoustic
wave to yield a spectrum thereof; (c) determining whether the spectrum
includes a spectral signature, thus yielding a determination, wherein the
spectral signature is present when a device in the ice-making machine is
operating; and (d) issuing an alert based on the determination.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011]FIG. 1 is a functional block diagram of a system implemented in an
ice-making machine.

[0012]FIG. 2 is a functional block diagram of control board in the system
of FIG. 1.

[0013] FIGS. 3A and 3B are, together, a flowchart of an ice-sensing
process that is implemented on the control board of FIG. 2.

[0014]FIG. 4 is a flowchart of a system diagnostics process that is
implemented on the control board of FIG. 2.

[0015] FIG. 5 is a block diagram of a system that executes the operations
of the ice-sensing process of FIG. 2 and the system diagnostics process
of FIG. 3.

[0019] A component or a feature that is common to more than one drawing is
indicated with the same reference number in each of the drawings.

DESCRIPTION OF THE PREFERRED EMBODIMENT

[0020]FIG. 1 is a functional block diagram of a system, referred to
herein as system 100, implemented in an ice-making machine. System 100
performs various digital signal processing operations on an acoustic
signal from an ice thickness sensor, using a fast Fourier transform (FFT)
algorithm, for increasing reliability of ice detection and for providing
enhanced system diagnostics on the ice-making machine.

[0021] System 100 includes an evaporator 102, a compressor 104, a water
pump, i.e., pump 106, a control board 130 and a solenoid 160. Evaporator
102 includes a sensor 110. Control board 130 includes a microphone 140, a
processing module 145 and a relay 150. The term "module" is used herein
to denote a functional operation that may be embodied either as a
stand-alone component or as an integrated configuration of a plurality of
sub-ordinate components.

[0022] System 100 runs through an ice-making cycle that includes a
pre-chill stage, a freeze stage, a harvest stage and a purge stage.

[0023] Evaporator 102 is a structure for forming ice thereon. Pump 106
pumps and circulates water 115, in a liquid state, so that water 115
flows over evaporator 102 and collects as a body of water, i.e., water
103 (in FIG. 1, represented with a perimeter having a dashed line), that
is being frozen into a solid state, i.e., ice.

[0024] Evaporator 102 has a coil (not shown) through which is routed
either of a cold gas or a hot gas. Compressor 104 facilitates the routing
of the cold gas through the coil. When the cold gas is routed through the
coil, water 103 freezes, thus forming as ice on evaporator 102. In
practice, water 115 cascades over evaporator 102, and freezes gradually,
so that water 103 forms into a block of ice. After water 103 forms as
ice, the hot gas is routed through the coil, thus heating evaporator 102
and slightly melting the ice so that the ice, and more particularly water
103 in the form of ice, can be removed.

[0025] Evaporator 102 may also include a grid (not shown) for holding
water 103 and forming water 103 in the shape of cubes, or any other
desired shape.

[0026] Compressor 104, during operation, emits a mechanical vibration 105,
and pump 106, during operation, emits a mechanical vibration 107. Each of
mechanical vibration 105 and mechanical vibration 107 propagates through
physical structures in system 100, and through water 103, as an acoustic
wave 108. Thus, acoustic wave 108 may include contributions from either
or both of mechanical vibration 105 and mechanical vibration 107.

[0028] Processing module 145, based on its analysis of detected acoustic
wave 117, determines whether water 103 has formed into ice, and if yes,
issues a signal 124 to remove water 103, as ice, from evaporator 102.
More particularly, when processing module 145 has determined that water
103 has formed into ice, processing module 145 issues signal 124 to relay
150, which in turn issues an actuation signal 155 that energizes solenoid
160. Energizing solenoid 160 causes the routing of the hot gas through
the coil of evaporator 102, which causes water 103 to slightly melt and
become free from evaporator 102. The removal of the ice is also referred
to as harvesting.

[0029] As noted above, acoustic wave 108 may include contributions from
either or both of mechanical vibration 105 and mechanical vibration 107.
Accordingly, either of mechanical vibration 105 or mechanical vibration
107 could be the source of acoustic wave 108, and as such, could be the
source of detected acoustic wave 117 for the analysis performed by
processing module 145.

[0030] Each of mechanical vibration 105 and mechanical vibration 107 is
unique, and as such, provides a unique spectral signature for each of
compressor 104 and pump 106. Processing module 145 analyzes detected
acoustic wave 117 and draws some conclusions about the operations of
compressor 104 and pump 106. For example, processing module 145, by way
of communications with other components of system 100, knows in which
ice-making stage system 100 is operating, and also knows when compressor
104 should turn ON, and when compressor 104 should turn OFF. Accordingly,
processing module 145, based on its analysis of detected acoustic wave
117, also determines whether compressor 104 turns ON or OFF at its
appropriate times. If processing module 145 determines that compressor
104 is not operating properly, then processing module 145 issues an alert
signal 165. Alert signal 165 could be manifested, for example, as a fault
indicator on a user interface (not shown in FIG. 1). Processing module
145 makes a similar determination for the operation of pump 106, and
alert signal 165 indicates the operating status of pump 106.

[0031]FIG. 2 is a functional block diagram of control board 130, and
shows further details of processing module 145. Processing module 145
includes a micro-controller 205, and a digital signal processing module
210.

[0033] In accordance with ice-sensing process 215, digital signal
processing module 210 analyzes digital signal 208 to determine whether
water 103 has formed into ice, and if yes, issues signal 124 to relay
150, which in turn issues actuation signal 155. Ice-sensing process 215
is described in greater detail below, with reference to FIGS. 3A and 3B.

[0034] In accordance with system diagnostics process 220, digital signal
processing module 210 analyzes digital signal 208 to draw conclusions
about the operations of compressor 104 and pump 106, and if necessary,
issues alert signal 165. System diagnostics process 220 is described in
greater detail below, with reference to FIG. 4.

[0035] In some situations, issues can occur in transmitting sound through
tubes or connectors, or through a component making inadvertent contact
with another component. Such an issue can trigger a false harvest signal.
These issues can be avoided by embedding microphone 140 in a probe with
sensor 110, i.e., an integrated sensor microphone, that comes into
contact with the ice (i.e., the body of water) or the evaporator, or is
situated in close proximity, e.g., less than 0.5 inches, to the ice
(i.e., the body of water) or the evaporator.

[0036] For example, in the context of the components shown in FIG. 1,
microphone 140 and sensor 110 could be integrated together, thus
resulting in an integrated sensor microphone. Accordingly, there will be
no need for microphone 140 on control board 130, and no need for acoustic
wave conduit 120. The integrated sensor microphone avoids issues with
transmission of sound from sensor 110 to microphone 140, and thus
eliminates any chance of extraneous noise and vibration through acoustic
wave conduit 120 to control board 130, and improves the signal to noise
ratio. Additionally, the entire integrated sensor microphone can be
hermetically sealed to eliminate any chance of moisture entering sensor
110 or microphone 140, and thus adversely impacting the performance of
sensor 110 or microphone 140.

[0037] An alternative to the integrated sensor microphone is an integrated
sensor accelerometer that employs an accelerometer instead of microphone
140. In the integrated sensor accelerometer, the accelerometer is used to
measure the vibration transmitted through sensor 110. The accelerometer
converts the vibration energy into an electrical signal that is
transmitted to control board 130.

[0038] Either of the integrated sensor microphone or the integrated sensor
accelerometer could be regarded as a sensing probe, and be situated on
evaporator 102 in place of the stand-alone sensor 110. The sensing probe
produces an electrical signal, similar to analog electrical signal 122,
that is coupled into processing module 145. An exemplary embodiment of
such a sensing probe is described in greater detail below, with reference
to FIGS. 6-8.

[0042] The magnitude of detected acoustic wave 117 is dependent upon the
magnitude of acoustic wave 108, which is in turn dependent upon
magnitudes of mechanical vibration 105 and mechanical vibration 107, and
thus dependent on physical factors such as the size of system 100. As
such, the magnitude of detected acoustic wave 117, and quantities derived
from the magnitude of detected acoustic wave 117 are dependent on the
size of system 100.

[0045] In step 340, digital signal processing module 210 extracts one or
more frequency components of interest, and their respective magnitudes,
from FFT array 332. For example, digital signal processing module 210
extracts a fundamental frequency component, a second harmonic of the
fundamental frequency component, and a third harmonic of the fundamental
frequency component, and magnitudes for each of the fundamental
frequency, second harmonic and third harmonic. The fundamental frequency
would be, for example, either of a fundamental frequency of mechanical
vibration 105 or a fundamental frequency of mechanical vibration 107.
From step 340, ice-sensing process 215 progresses to step 350.

[0046] The fundamental frequency of mechanical vibration 105 and the
fundamental frequency of mechanical vibration 107 may be inherent
properties of compressor 104 and pump 106, and therefore, known in
advance. Otherwise, these fundamental frequencies could be obtained
through observation, or during a learning mode of ice-sensing process
215. For example, to learn the fundamental frequency of mechanical
vibration 105, digital signal processing module 210, by way of
communications with other components of system 100, would (a) turn OFF
compressor 104 and evaluate a first spectrum of detected acoustic wave
117, and then (b) turn ON compressor 104 and evaluate a second spectrum
of detected acoustic wave 117. The fundamental frequency of mechanical
vibration 105 would appear as a dominant frequency component in the
second spectrum, but not in the first spectrum. Alternatively, rather
than digital signal processing module 210 controlling the ON/OFF states
of compressor 104, system 100 may proceed in a regular mode of operation
and notify digital signal processing module 210 when compressor 104 is ON
or OFF.

[0047] In the next couple of steps, in the early part of the freeze stage,
for example, within the first two minutes, before water 103 has formed as
block of ice, digital signal processing module 210 obtains ambient
acoustic levels of the frequencies of interest. Although in the present
example, the early part of the freeze stage is regarded as a period of
two minutes, other time durations are possible, e.g., six minutes.

[0048] In step 350, digital signal processing module 210 considers whether
the freeze stage is in its early part. If the freeze stage is in its
early part, then ice-sensing process 215 progresses from step 350 to step
354. If the freeze stage is not in its early part, then ice-sensing
process 215 branches from step 350 to step 360.

[0049] In step 354, which is performed when the freeze stage is in its
early part, digital signal processing module 210 stores the frequency
components of interest, and their magnitudes, in a threshold array 352.
From step 354, ice-sensing process 215 loops back to step 320.

[0050] By looping back to step 320, and progressing through steps 330,
340, 350 and 354, ambient acoustic levels of the frequencies of interest
are repeatedly captured and stored in threshold array 352.

[0051] In step 360, which is performed when the freeze stage is not in its
early part, for each of the frequencies of interest having magnitudes in
threshold array 352, digital signal processing module 210 calculates an
average magnitude, and stores the average magnitude in an average
magnitude array 361. To the average magnitude, digital signal processing
module 210 adds a margin, e.g. 3 decibels (dB), thus yielding a resultant
threshold, and stores the resultant threshold into an ice detection
threshold array 362. Ice detection threshold array 362 will thus hold a
resultant threshold for each of the frequencies of interest. From step
360, ice-sensing process 215 progresses to step 365.

[0052] In step 365, digital signal processing module 210 tests for
failures of sensor 110, microphone 140 (or the accelerometer being used
in place of microphone 140) or, in the case of these components being
integrated together, the sensing probe, collectively referred to as ice
probe faults. Accordingly, for each of the frequency components of
interest, digital signal processing module 210 calculates a standard
deviation of the average magnitudes in average magnitude array 361. For
each of the frequency components of interest, the standard deviation is
compared to a probe fault lower threshold 363, and a probe fault upper
threshold 364. If for any of the frequency components of interest, the
standard deviation is less than probe fault lower threshold 363 or
greater than probe fault upper threshold 364, there is assumed to be a
fault of one or more of sensor 110, microphone 140 (or the accelerometer
being used in place of microphone 140) or, in the case of these
components being integrated together, the sensing probe. Although step
365 is being described as part of ice sensing process 215, it could be
performed as part of system diagnostics 220.

[0053] As mentioned above, the magnitude of detected acoustic wave 117,
and quantities derived from the magnitude of detected acoustic wave 117
are dependent on the size of system 100. Accordingly, appropriate values
for probe fault lower threshold 363 and probe fault upper threshold 364
would be determined through experimentation.

[0054] From step 365, if the test passes, i.e., no fault is detected, then
ice-sensing process 215 progresses to step 370. If the test fails, i.e.,
a fault is detected, then ice- sensing process 215 progresses to step
366.

[0055] In step 366, digital signal processing module 210 issues an ice
probe fault alert, for example, by way of alert 165. Although step 366 is
being described as part of ice sensing process 215, it could be performed
as part of system diagnostics 220.

[0056] In step 370, as water 103 continues to freeze, digital signal
processing module 210 captures and processes real-time samples of
detected acoustic wave 117. More specifically, digital signal processing
module 210 extracts, from detected acoustic wave 117, frequency
components of interest, and their respective magnitudes. For a better
signal-to-noise ratio (SNR), and therefore better data integrity, average
real-time magnitudes are considered over a period of time, e.g., mean of
five FFT magnitude values obtained over a one-second interval of time.
From step 370, ice-sensing process 215 progresses to step 380.

[0057] In step 380, digital signal processing module 210 compares the
magnitudes of the real-time frequency components of interest to their
corresponding magnitudes in ice detection threshold array 362. This
comparison is being made because, when water 103 is adequately formed as
a block of ice, the real-time magnitudes of the frequencies of interest
will be significantly greater than they were before the ice was formed.

[0058] In step 380, if none of the real-time magnitudes is greater than
its corresponding magnitude in ice detection threshold array 362, then
digital signal processing module 210 concludes that water 103 is not yet
sufficiently frozen, and digital signal processing module 210 loops back
to step 370.

[0059] In step 380, if, for any of the frequency components of interests,
the real-time magnitude is greater than its corresponding magnitude in
ice detection threshold array 362, then digital signal processing module
210 concludes that water 103 is sufficiently frozen, and digital signal
processing module 210 progresses to step 390.

[0060] Referring still to step 380, although the progression to step 390
is described as occurring in a case where, for any of the frequency
components of interests, the real-time magnitude is greater than its
corresponding magnitude in ice detection threshold array 362, the test
can be based on some other minimum number of frequency components of
interest having real-time magnitudes greater than their corresponding
magnitudes in ice detection threshold array 362. For example, the test
may require that at least two out of three frequency components of
interest have real-time magnitudes greater than their corresponding
magnitudes in ice detection threshold array 362.

[0061] In step 390, digital signal processing module 210 issues signal 124
to relay 150, which in turn issues actuation signal 155 to energize
solenoid 160. Energizing solenoid 160 results in the harvesting, i.e.,
removing, of water 103, in the form of ice, from evaporator 102.

[0062]FIG. 4 is a flowchart of system diagnostics process 220. As
mentioned above, in accordance with system diagnostics process 220,
digital signal processing module 210 analyzes digital signal 208 to draw
conclusions about the operations of compressor 104 and pump 106, and if
necessary, issues alert signal 165. In brief, digital signal processing
module 210 evaluates acoustic signatures of devices within system 100 to
determine whether or not the devices are energizing at appropriate times.
Below, system diagnostics process 220 is described with regard to
operations of compressor 104 and pump 106. However, system diagnostics
process 220 can be employed to evaluate operations of any device in
system 100 that generates a mechanical vibration (e.g., a dump valve, a
harvest solenoid, and a water inlet valve). System diagnostics process
220 commences with step 410.

[0066] In step 435, digital signal processing module 210 considers whether
either of compressor 104 or pump 106 should be energized in the present
stage of the ice-making cycle. That is, digital signal processing module
210, by way of communications with other components of system 100, knows
whether either of compressor 104 or pump 106 should be energized. If
either of compressor 104 or pump 106 should not be energized, then system
diagnostics process 220 loops back to step 430. If either of compressor
104 or pump 106 should be energized, then system diagnostics process 220
progresses to step 440.

[0067] In step 440, digital signal processing module 210 determines
whether the spectrum from step 430 includes a spectral signature of the
device, i.e., compressor 104 or pump 106, that should be energized. For
example, assume that compressor 104 should be energized. Accordingly,
digital signal processing module 210 determines whether spectrum array
432 includes the spectral signature of compressor 104 that is stored in
spectral signature array 425. From step 440, system diagnostics process
220 progresses to step 450.

[0068] In step 450, if spectrum array 432 includes the spectral signature
of the device being considered, e.g., compressor 104, then digital signal
processing module 210 concludes that system 100 is operating properly,
and accordingly system diagnostics process 220 loops back to step 430. If
spectrum array 432 does not include the spectral signature of the device
being considered, then digital signal processing module 210 concludes
that system 100 is not operating properly, and accordingly system
diagnostics process 220 progresses to step 460.

[0069] Referring still to step 450, recall that spectral signature array
425 contains a spectral signature for each of compressor 104 and pump
106. Accordingly, digital signal processing module 210 can therefore
determine whether detected acoustic signal 117 includes either or both of
mechanical vibration 105 and mechanical vibration 107. This also enables
system diagnostics process 220 to distinguish between spectral
contributions from compressor 104 and pump 106, and determine whether
either or both of compressor 104 and pump 106 is ON, and therefore
diagnose operations of either or both of compressor 104 and pump 106.
Moreover, digital signal processing module 210 can make these
determinations even in a case where detected acoustic signal 117 includes
noise or spectral contributions from other devices in system 100.

[0071] Digital signal processing module 210 is described above as issuing
alert signal 165 for a case where a device that is being considered is
expected to be ON, but spectrum array 432 does not include the spectral
signature of the device being considered. However, system diagnostics
process 220 could be configured so that digital signal processing module
210 issues alert signal 165 in a case where a device is expected to be
OFF, and so, the spectrum should not include the spectral signature of
the device, but instead spectrum array 432 does include the spectral
signature of the device. This situation could occur, for example, in a
case where either system 100 fails to turn OFF the device, or the device
is stuck in its ON state.

[0072] In review, system 100 includes a detector, i.e., sensor 110, and a
processor, i.e., processing module 145. Sensor 110 detects acoustic wave
108, which is propagating through a body of water, i.e., water 103, as
water 103 is being frozen on a structure, i.e., evaporator 102, in an
ice-making machine, thus yielding detected acoustic wave 117.

[0073] Processing module 145: extracts, from detected acoustic wave 117,
(a) a frequency component thereof, and (b) a magnitude of the frequency
component; and issues a signal, i.e., signal 124, to remove water 103
from evaporator 102 when the magnitude exceeds a threshold value.

[0074] Processing module 145 also: analyzes detected acoustic wave 117 to
yield a spectrum thereof; determines whether the spectrum includes a
spectral signature, thus yielding a determination, wherein the spectral
signature is present when a device, e.g., compressor 104, in the
ice-making machine is operating; and issues an alert, i.e., alert signal
165, based on the determination.

[0075] Detected acoustic wave 117 is a time-domain signal. Processing
module 145, to extract the frequency component and the magnitude:
transforms the time-domain signal to a frequency-domain signal; and
obtains the frequency component, and the magnitude, from the
frequency-domain signal.

[0076] Also in system 100, the threshold value against which the magnitude
is compared may be regarded as a first threshold value, and accordingly,
processing module 145: also extracts, from detected acoustic wave 117,
(a) a harmonic of the frequency component, and (b) a magnitude of the
harmonic; and issues signal 124 to relay 150 when both of (i) the
magnitude exceeds the first threshold value, and (ii) the magnitude of
the harmonic exceeds a second threshold value.

[0077] System 100 is described above with processing module 145 being
implemented on control board 130. As such, processing module 145, or any
of its components, and in particular digital signal processing module
210, may be implemented in hardware (e.g., electronic circuitry) or
firmware, or a combination thereof. Moreover, digital signal processing
module 210 can be implemented in software, and run on a computer that is
in communication with other components in system 100.

[0078] FIG. 5 is a block diagram of a computer-implemented embodiment,
hereinafter referred to as system 500, of digital signal processing
module 210. System 500 includes a computer 505 that in turn includes a
processor 515 and a memory 520. System 500 is in communication with other
components in system 100.

[0079] Processor 515 is an electronic device configured of logic circuitry
that responds to and executes instructions.

[0080] Memory 520 is a computer-readable medium encoded with a computer
program. In this regard, memory 520 stores data and instructions that are
readable and executable by processor 515 for controlling the operation of
processor 515. Memory 520 may be implemented in a random access memory
(RAM), a hard drive, a read only memory (ROM), flash memory, or a
combination thereof. One of the components of memory 520 is a program
module 525.

[0081] Program module 525 contains instructions for controlling processor
515 to execute the methods described herein. That is, instructions from
program module 525, when read by processor 515, cause processor 515 to
perform operations of ice-sensing process 215, and system diagnostics
process 220.

[0082] Although program module 525 is described herein as being installed
in memory 520, and therefore being implemented in software, it could be
implemented in any of hardware (e.g., electronic circuitry), firmware,
software, or a combination thereof.

[0083] Processor 515 outputs a result of an execution of the methods
described herein, for example, a fault indicator based on the issuance of
alert signal 165. Alternatively, processor 515 could direct the output to
a remote device (not shown) via a network (not shown).

[0084] While program module 525 is indicated as being already loaded into
memory 520, it may be configured on a storage medium 535 for subsequent
loading into memory 520. Storage medium 535 is also a computer-readable
medium that stores program module 525 thereon. Examples of storage medium
535 include a floppy disk, a compact disk, a magnetic tape, a read only
memory, an optical storage media, universal serial bus (USB) flash drive,
a digital versatile disc, or a zip drive. Alternatively, storage medium
535 can be a random access memory, or other type of electronic storage,
located on a remote storage system and coupled to computer 505 via a
network (not shown).

[0085] As mentioned above, microphone 140 and sensor 110 could be
integrated together, thus resulting in an integrated sensor microphone,
and an alternative to the integrated sensor microphone is an integrated
sensor accelerometer that employs an accelerometer instead of microphone
140. Either of integrated sensor microphone or the integrated sensor
accelerometer could be regarded as a sensing probe.

[0086]FIG. 6 is a cross-section view of a sensing probe 605 on evaporator
102. Sensing probe 605 includes a dimple 610 that is implemented as a
part of sensor 110 and that contacts water 103 on evaporator 102.

[0088]FIG. 8 is a cross-section view of sensing probe 605 configured as
an integrated sensor microphone having microphone 140 embedded into a top
opening.

[0089] The techniques described herein are exemplary, and should not be
construed as implying any particular limitation on the present
disclosure. It should be understood that various alternatives,
combinations and modifications could be devised by those skilled in the
art. For example, system 100 may include a plurality of sensors 110 for
detecting acoustic wave 108 at various locations on water 103, and steps
associated with the processes described herein can be performed in any
order, e.g., order of steps 435 and 430 can be reversed, unless otherwise
specified or dictated by the steps themselves. Also, although acoustic
wave 108 is described herein as resulting from mechanical vibrations of
either compressor 105 or pump 107, system 100 could include a
special-purpose device that generates a particular vibration for analysis
by processing module 145. The present disclosure is intended to embrace
all such alternatives, modifications and variances that fall within the
scope of the appended claims.

[0090] The terms "comprises" or "comprising" are to be interpreted as
specifying the presence of the stated features, integers, steps or
components, but not precluding the presence of one or more other
features, integers, steps or components or groups thereof.